Data processing has been revolutionized in recent years, and these changes present tremendous possibilities. For example, if we consider a variety of use cases — from the IoT and Artificial Intelligence to user activity monitoring, fraud detection and FinTech — what do all of these cases have in common? They all collect and process high volumes of data, which arrive at high velocities. After processing this data, these technologies then deliver them to all the appropriate consumers of data.
Last month, with the release of version 5.0, Redis launched an innovative new way to manage streams while collecting high volumes of data — Redis Streams. Redis Streams is a data structure that, among other functions, can effectively manage data consumption, persist data when consumers are offline with a data fail-safe, and create a data channel between many producers and consumers. It allows users to scale the number of consumers using an app, enables asynchronous communications between producers and consumers and efficiently uses main memory. Ultimately, Redis Streams is designed to meet consumers’ diverse needs, from real-time data processing to historical data access, while remaining easy to manage.
Redis Streams offers several possibilities for users, including the ability to integrate this new data structure into various apps. In order to make it easier for users to start using Redis Streams, we have written up a few tutorials to help get you started:
We hope that these three articles will help you get a better grasp on how Redis Streams can be used — and how you can optimize data processing with Redis Streams as a tool. Data is currently being produced at faster rates than ever, which in turn produces new challenges. Over at Redis Labs, we hope that innovations like Redis Streams can help our users tackle these challenges head-on. If you have any questions about how to use Redis Streams or any of our other tools, please don’t hesitate to contact us at email@example.com.